Concept Based Query Expansion

Boubacar, Abdoulahi; Niu, Zhendong

doi:10.1109/skg.2013.10

Cited by 7 publications

(2 citation statements)

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“…To address these challenges, early query augmentation efforts primarily focused on employing query expansion techniques to boost retrieval performance. One approach involved using global models to pinpoint and incorporate concepts relevant to a query [26]. Another strategy harnessed lexical-semantic relationships to identify terms semantically related to the query [27].…”

Section: ) Query Augmentationmentioning

confidence: 99%

Information Retrieval: Recent Advances and Beyond

Hambarde

Proença

2023

IEEE Access

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This paper provides an extensive and thorough overview of the models and techniques utilized in the first and second stages of the typical information retrieval processing chain. Our discussion encompasses the current state-of-the-art models, covering a wide range of methods and approaches in the field of information retrieval. We delve into the historical development of these models, analyze the key advancements and breakthroughs, and address the challenges and limitations faced by researchers and practitioners in the domain. By offering a comprehensive understanding of the field, this survey is a valuable resource for researchers, practitioners, and newcomers to the information retrieval domain, fostering knowledge growth, innovation, and the development of novel ideas and techniques.INDEX TERMS First-stage retrieval, information retrieval, second-stage retrieval.

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Section: ) Query Augmentationmentioning

confidence: 99%

Information Retrieval: Recent Advances and Beyond

Hambarde

Proença

2023

IEEE Access

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“…In [34] the word sense disambiguation is used to get the sense of a word in the given query context. Search terms are actually independently considered and these search terms are extended with some synonyms from thesaurus [36], which will some times bring a large amount of undesirable results. So a statistical co-occurrence is proposed.…”

Section: Querying Processingmentioning

confidence: 99%

SodhanaRef: a reference management software built using hybrid semantic measure

Kiran

Reddy

2018

IJET

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Reference management softwares are widely used by the researchers to maintain their collection of scholarly literature that exist in PDF format. Though widely used most of the reference management softwares have no sophisticated Information retrieval except few which offer advanced search that includes search for title, author etc., These softwares in the present day market do not give importance to the semantic similarity or relatedness concept, query expansion and finding the context within the query to find the concept behind the user mentioned query.With SodhanaRef, a solution is offered to deal with the above-mentioned issues by building reference management software using a mix up of corpus-based and knowledge-based semantic measures. Based on the evolution done on about 200 various scholarly literatures in the PDF form, SodhanaRef shows a good performance over Mendeley when compared between these two reference management softwares for title search. The other evaluations for finding the semantic similarity between the user mentioned query and the existing titles in the title search and for identifying the concept behind the query along with identifying the concept of a research publication have shown good results with an average precision between 0.8 to 1 for each query.

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Conceptual Clustering

Boubacar

Niu

2014

Lecture Notes in Electrical Engineering

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Concept Based Query Expansion

Cited by 7 publications

References 0 publications

Information Retrieval: Recent Advances and Beyond

Information Retrieval: Recent Advances and Beyond

SodhanaRef: a reference management software built using hybrid semantic measure

Conceptual Clustering

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